nuthatch

io.github.nightswatchhqv4.0.0Updated Oct 1, 2026

Query an EVM contract's indexed history with SQL, via a local nuthatch nest and nuthatch dev.

Overview

AI-generated overview

Lets an assistant query an EVM contract's locally indexed history with SQL through a built-in MCP server.

What it does
nuthatch indexes an EVM contract's events into a local SQL database (a "nest") and exposes a compiled-in MCP server so an assistant can run SQL against that data. Tables are generated from the contract ABI, with one table per event, and queries span both the live tip and sealed history. The MCP server carries the same degraded-nest notices and query hints as the CLI and HTTP API.
When to use it
Use it when you want an assistant to answer questions about a specific contract's on-chain history in plain English, with the data kept on your own machine and no hosted service. It suits analytics, dashboards, and agent workflows over one or more contracts.
Requirements
A local nuthatch binary (prebuilt for macOS Apple Silicon and Linux x86_64, or built from source with Rust 1.95.0) plus a running nest started with nuthatch dev. Needs a JSON-RPC endpoint for the chain; bundled public endpoints are for testing only, and a paid provider or your own node is expected for real use. Linux needs glibc 2.34+ and libstdc++ from GCC 11+.
Before you install
The MCP server queries a local nest; the underlying indexer reads the chain over JSON-RPC, and a provider may charge for that endpoint. Public endpoints are rate-limited, shared, and may prune old state, so deep backfills can stall or fail. Older releases had an arbitrary file read and an arbitrary file write on /sql; be on a current release and read SECURITY.md before exposing /sql to anyone you do not trust.

Installation

In SourceWeft

  1. Open nuthatch in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

nuthatch

Turn an EVM contract's history into a local SQL database. One Rust binary, no Postgres, no subgraph to write, and an MCP server built in.

[ci] · Website: www.nuthatch-indexer.com

sh
curl -fsSL https://nuthatch-indexer.com/install.sh | sh                  # macOS Apple Silicon, Linux x86_64nuthatch init 0xA0b86991c6218b36c1D19D4a2e9Eb0cE3606eB48 --alias usdc   # USDC; the chain is detectednuthatch dev --backfill 300                                             # the last 300 blocks, then keeps upnuthatch sql "SELECT count(*) FROM usdc__transfer"                      # in a second terminal

The Linux binary needs glibc 2.34 or newer to run (it is built on 2.35). No Intel Mac binary is published: there, and on other platforms, build from source with Rust 1.95.0 (docs/install.md). init creates a nest: a directory holding the contract's ABI, its config and, once dev runs, its indexed data. --backfill 300 starts 300 blocks behind the tip, about an hour of mainnet, so there are rows to query within seconds on the bundled public endpoints. Without it, dev backfills from the contract's deployment block: for USDC that is 20 million blocks, a long backfill on free public endpoints and a job for your own RPC (--rpc).

Needs a subgraphNeeds handler codeData comes fromWhat you runQuery with
The Graphyesyes (AssemblyScript)indexers on the networknothing, or graph-node + Postgres + IPFSGraphQL
Pondernoyes (TypeScript)your RPC endpointNode.js, plus Postgres in productionSQL, GraphQL
nuthatchnono: tables come from the ABIyour RPC endpointone binarySQL, HTTP, MCP

Like Ponder, nuthatch reads the chain over JSON-RPC, so it needs an endpoint, and a provider may charge for one. The public endpoints it bundles are for trying it out, not for keeping it running. It complements The Graph rather than replacing it: a subgraph serves an application from a network of indexers, while a nest puts a contract's history in a database on your own machine.

Why. Getting at a contract's history usually means writing a subgraph or handler code, running a database, or renting someone else's copy. nuthatch generates the tables from the ABI, runs as one process with nothing else to install, and keeps the data on your machine: at most 2 GB of RAM per chain, no telemetry, no account. The built-in MCP server lets Claude or any MCP client query it.


What you get

  • No authoring. init 0xAddr resolves the ABI (Sourcify, then Etherscan), generates the schema and decoders, and scaffolds the project. You write nothing.
  • No infra. A single static Rust binary. Embedded mode needs no Postgres, no Docker, no IPFS.
  • It's just SQL. Your contract's events become per-event tables you query with real analytical SQL - the live tip and sealed history, one surface.
  • It's yours, and it's small. ≤2 GB RAM for single-chain tip-following, CI-enforced. No telemetry, no phone-home, no mandatory API token, ever.

Who runs it

  • Lodestar, an analytics dashboard for The Graph Protocol on Arbitrum One, serves live panels from self-hosted nests instead of The Graph gateway.

An earlier example, now finished: Arcaidia, a speed layer over Circle's CCTP built at ETHOnline 2026, read its indexed state from two nests on Ethereum Sepolia and Arc Testnet. Its solver discovered intents there, its settlement agent tracked CCTP there, and its web console rendered from them. The nests were serving within two hours of the builder asking The Graph for a higher Studio rate limit. They were stopped on 2026-09-29.

More at nuthatch-indexer.com/stories.

Nightswatch does not run a hosted nest service. GraphOps plans to offer hosted nests on its own platform, running the same binary as anyone else; there is no date for it yet.


Install

sh
curl -fsSL https://nuthatch-indexer.com/install.sh | sh

That downloads the prebuilt binary for your platform from the latest release, verifies its SHA-256, and installs it to ~/.local/bin (override with NUTHATCH_INSTALL_DIR). No compiler is involved. Prebuilt binaries cover macOS Apple Silicon and Linux x86_64 and are attached to every release with their checksums, if you would rather fetch one by hand. No Intel Mac binary is published; the installer says so and points at the source build below.

The Linux binary is dynamically linked and needs two things, both measured off the published artifact with objdump -T rather than inferred:

  • glibc 2.34 or newer - the measured ABI floor. The release is built on glibc 2.35, but the binary references no symbol newer than GLIBC_2.34: 2.34 is what you need to run it, 2.35 is what we compile it on (#978).
  • libstdc++ from GCC 11 or newer (GLIBCXX_3.4.29, CXXABI_1.3.13), because the binary embeds DuckDB, which is C++, so it links libstdc++.so.6 alongside libc, libm and libgcc.

Debian 12, Ubuntu 22.04, RHEL 9 and Amazon Linux 2023 clear both.

Verify who built it. Every release binary carries a build provenance attestation, which a checksum cannot give you:

sh
gh attestation verify nuthatch-x86_64-unknown-linux-gnu.tar.gz --repo nightswatchhq/nuthatch

From source, which is the only route on a platform we do not publish a binary for, Intel Macs included (the Intel build has not been verified on Intel hardware):

sh
rustup toolchain install 1.95.0cargo +1.95.0 install --git https://github.com/nightswatchhq/nuthatch nuthatch

The +1.95.0 is required: cargo install --git ignores the repo's toolchain pin, and a newer default toolchain fails to compile a dependency.

Container images are published per release to ghcr.io/nightswatchhq/nuthatch - :<version> for embedded, :<version>-scaled for the scaled build. The image ships the same binary attached to the release, so the two cannot drift.

docs/install.md has the detail behind each of these: why the two ABI floors are different numbers, what the attestation proves and what --repo is for, and why the toolchain pin exists.

Chains. Ethereum, Arbitrum One, Base, BSC, Polygon, Gnosis, Optimism, Monad and Robinhood Chain are built in, with measured public endpoints and tuned finality settings - omit --chain and nuthatch probes each for your contract's bytecode and picks the one it lives on. Point at your own node with --rpc.

Any other EVM chain works too - World Chain, Base Sepolia, your own devnet. Name the chain and say where it lives:

sh
nuthatch init 0xADDR --chain world-chain --rpc https://your-endpoint.example

The chain id is read from the endpoint itself, so there is no id to look up and nothing to type wrong. A built-in chain never dials to learn its id: on one of the nine names --rpc is not consulted for the chain id, but it is the pool - your endpoints replace the bundled public ones outright, and nothing public is appended after them. Omit --rpc on an unregistered name and the refusal tells you the remedy rather than just listing the built-ins.

Public endpoints are a moving target, and the ones shipped here are measured rather than assumed - but a measurement is a snapshot, not a property. Run nuthatch doctor --rpc <url> before trusting a long backfill to any endpoint, yours or ours: it reports the widest eth_getLogs range, the JSON-RPC batch limit and whether the node has archive depth, and prints the largest safe --window.

Everything downstream was always chain-agnostic - dev, sql and bench, and the indexer's unregistered-chain finality and window defaults. init's allow-list was the only thing narrower than what nuthatch actually scaffolds, and it went in 2.4.0. See running an unlisted EVM chain for the finality caveat, which is the part worth reading: a chain whose finalized tag runs close to the tip needs a depth-based policy instead, or you seal immutable Parquet that could never be corrected.

Bring your own RPC endpoint

nuthatch assumes a paid RPC endpoint, or your own node, for anything you intend to keep running. That is the golden path.

Worth knowing, since we are being precise about it: most figures currently in docs/benchmarks.md were measured against public endpoints, and that is a known weakness of those numbers rather than a recommendation - a benchmark taken through a rate-limited endpoint measures the endpoint. We measured the network at 99.3% of backfill wall clock, which is why the replay rig (RFC-0039) exists and why those figures carry that caveat on the page itself.

The free public endpoints bundled per chain exist for one job: so init → dev works with zero setup, which is the two-minute demo, and it is deliberate. Treat them as testing and initial validation - trying it out, checking a contract resolves, following the tip of something quiet. They are the on-ramp, not the road.

Why they are not fine for real work, said here rather than discovered at 3am:

  • They are rate-limited and shared. You are queueing behind everyone else using the same free tier from the same IP range. Throughput varies by the hour.
  • They fail intermittently, and not always loudly. A rate-limited endpoint may return an empty result rather than an error. nuthatch fails over across the pool and retries, but a window that every endpoint refuses will stall until one recovers - /ready reports stalled when that happens.
  • Deep backfills will crawl or stop. Full history over a busy contract means millions of eth_getLogs calls. Expect a free endpoint to throttle you long before that finishes.
  • No archive guarantees. Many free endpoints prune old state, so a backfill from a 2020 deploy block can simply fail partway.

Check an endpoint before you trust a backfill to it. nuthatch doctor probes one and reports the largest getLogs window it will actually serve, its batch limit, and whether it has archive history - measured, not taken from the provider's documentation:

sh
nuthatch doctor --rpc https://your-endpoint.example --address 0xADDR

Use your own endpoint for anything you care about - your own node, or a paid provider:

sh
nuthatch init 0xADDR --chain arbitrum-one --rpc https://your-endpoint.example/arbitrumnuthatch dev --rpc https://your-endpoint.example/arbitrum   # or set rpc_urls in nuthatch.toml

--rpc is repeatable, and nuthatch round-robins across the pool with per-endpoint health tracking, so listing two or three endpoints gets you failover as well as throughput. Every endpoint in a pool must be on the same chain - nuthatch verifies this at startup and refuses to run against a mixed pool, since indexing against the wrong chain corrupts state silently.


Querying your data - the whole point

Every declared event becomes a table named {alias}__{event} (e.g. usdc__transfer), carrying the event's fields plus block_number, block_hash, block_timestamp, tx_hash, log_index, address and a _seq ordinal.

block_timestamp costs a block-header round trip per block - about 85% of backfill wall clock. A nest that will never ask a time-series question can drop the column with init --no-timestamps and skip that entirely. It is an init-time choice: changing it later is a breaking schema change and a full re-index, so it is worth a moment's thought and is deliberately not a flag you can flip. Details.

sh
# one-shot from the terminal (prints an aligned table; --json to pipe to jq)nuthatch sql 'SELECT "from" AS sender, count(*) AS n FROM usdc__transfer GROUP BY 1 ORDER BY n DESC LIMIT 5'
# or over HTTP, against a running `nuthatch dev`curl 'localhost:8288/sql?q=SELECT%20count(*)%20FROM%20usdc__transfer'
  • nuthatch sql queries the local store when dev is stopped, and transparently falls back to the running instance's API when dev holds it - the same command works either way.
  • A degraded nest says so. If a sealed segment is unreadable, nuthatch serves the rest of the table rather than failing your query - but it will not let that pass silently. /sql returns degraded and degraded_tables naming the affected tables, nuthatch sql prints a warning line, and the MCP server carries the same notice. The caveat is a fact about the nest, not about the row count you happened to get, so it appears whether or not this particular query touched the gap.
  • A failed query tells you how to fix it. A DuckDB error is classified against the nest's own schema and an actionable line is appended - the engine's raw message is always kept, the hint is added after it. An unknown table names the closest real one; a view that failed to build says so rather than reporting "does not exist" and sending you hunting for a missing view; and a Solidity bool column explains itself, because it is stored as exact text 'true'/'false' and therefore blows up inside COALESCE, CASE, UNION and bool_and/bool_or while comparing fine on its own. Same treatment on /sql, the MCP sql tool and the nuthatch sql REPL.
  • Hot + cold in one surface. Queries span the live unsealed tip (redb) and sealed history (Parquet), transparently - you never think about the boundary.
  • Big-int friendly. uint256 values are exact text; amounts that fit in 38 digits also get a {col}_dec DECIMAL view, so SUM(value_dec) works. Ids, nonces and hashes stay on the raw column: _dec is NULL for a full-width uint256.
  • AI-native. A Model Context Protocol server is compiled in (nuthatch mcp) - point Claude (or any MCP client) at your indexer and ask your contract's data in plain English, fully offline.

How fast is it

We ran someone else's benchmark rather than writing our own: Sentio's OBIB.

Case 1 indexes Transfer from LBTC across 22.2M Ethereum blocks.

wall clock74.8 s
events294,278 (matches Sentio's own README exactly)
RPC requests321
peak RSS320 MB

Case 2 is case 1's contract with per-account balances, and OBIB's implementations get them with one balanceOf() per account. We make none. For a plain ERC-20 the balance is the transfer history, so we index the token's whole life instead and derive it - trading 2.5M extra blocks of cheap getLogs for zero eth_call round trips.

wall clock49.2 s (median of 3)
accounts7,634 - OBIB's published figure, exactly
eth_call round trips0
RPC requests136
peak RSS325 MB

Reference times for the same case: Sentio 7.78 min, Envio 8.54 min, Subsquid 46.85 min.

Two caveats, stated rather than buried. First, this is deliberately not like-for-like on range: OBIB windows to 100,001 blocks, we index 2,611,334. On OBIB's own range we take 9.3 s - but that run cannot produce the case's output at all, because absolute balances need history from before the window, which is precisely why the benchmark makes the RPC calls. Second, "derived" is proven rather than asserted: at the pinned end block, 39 sampled accounts - the ten largest, ten smallest non-zero, ten zero-balance and ten by address order - all matched balanceOf(), including every zero-balance account, which is the case an off-by-one in the ledger would betray.

The count is 7,634 and not 7,635 because 0x0 is the mint/burn counterparty rather than a holder. That off-by-one was the tell that the interpretation was right.

Case 6 is the factory-template case: the Uniswap V2 factory over blocks 19,000,000-19,010,000, discovering pairs from PairCreated and indexing Swap on every child it finds. No per-child config, no redeploy, one rule.

wall clock49.5 s (median of 5)
events35,271 = 35,039 swaps, matching OBIB's expected count exactly, plus the 232 PairCreated rows
children discovered232
RPC requests16
peak RSS247 MB

For scale, OBIB's own published figures for case 6 differ between its two tables: the January 2026 results table gives Envio HyperIndex 1.92 min, Subsquid 5.34 min and Sentio 14.36 min, while the case-6 page reports Envio at 30 s from an earlier round. We are quoting both rather than the flattering one; on the second, Envio is faster than us. Note too that Envio and Subsquid serve this from their own pre-indexed networks, where nuthatch runs against plain JSON-RPC.

Both against a real provider (Alchemy), on an 11-core laptop. The artifacts are docs/bench/obib-case1.json, docs/bench/obib-case2.json and docs/bench/obib-case6.json; nuthatch bench backfill re-runs any of them. The case-2 nest is committed at obib-case2/ - keyless, so the endpoint arrives via --rpc, and verified to rebuild from a clean checkout. The case-6 nest is published at nightswatchhq/obib-case6 so the run can be reproduced rather than believed, and is submitted upstream as sentioxyz/open-blockchain-indexer-benchmark#3.

Wall clock on a shared endpoint is the provider's number as much as ours. The same case-6 range on the same commit measured anywhere from 17 s to 57 s depending on when it ran. We checked whether the fast runs were provider caching by re-running against an adjacent, never-fetched range (obib-case6-cold-control.json): it landed in the same band, so caching is not the explanation. The event count and the 16 RPC requests are invariant across every run, and they are the honest measure of range control.

Two things that number is worth knowing about:

  • It did not finish at all before v0.9.0. Alchemy returns its oversized-range refusal as HTTP 400, which our status classifier did not enumerate - so a window that needed splitting was retried unchanged, forever. Running an outside benchmark found a defect that our own testing had not.
  • ~85% of the original wall clock was buying block_timestamp - one serial round trip per block, for a column that workload never stores. Timestamps are now demand-driven and the log window adapts to what an endpoint will actually serve. See RFC-0029.

Case 6 found a defect too, in the harness rather than the indexer: bench backfill fetched a fixed address list, so a factory nest was measured without its children - 232 events in 2.6 s against an expected 35,039, reported as a success. Running an outside benchmark has now found two things our own testing did not.

Analytical queries run on DuckDB over sealed Parquet. We benchmark-gated the alternative rather than arguing about it: DataFusion measured 1.6–2.7× slower on the fold that matters, with the gap widening as segments grow, at exact result parity - RFC-0013 §5.


How it works (the 30-second version)

RPC ingestion  →  deterministic decode  →  redb hot store (tip)                                                            │                                        past finality  →  content-addressed Parquet segments                                                            │                                        DuckDB attaches segments read-only  →  SQL (hot ∪ cold)
  • Deterministic core. Decode, reorg handling, and entity derivation are deterministic and re-executable - same inputs, same content-addressed output. No LLM ever sits in the data path.
  • Reorg-safe by construction. Reorgs only ever touch the mutable hot store; sealed segments are strictly past finality and immutable.
  • Single writer. One ingestion thread writes; queries only ever attach read-only.

Point an AI at it

nuthatch has a Model Context Protocol server compiled in, so a coding agent can query your contract's data in plain English - offline, no phone-home. Wiring it is one step:

sh
nuthatch dev &                  # the index the agent will querynuthatch mcp --print-config     # prints a copy-paste config for Claude Code / any MCP client

Or add it to Claude Code directly:

sh
claude mcp add nuthatch -- nuthatch mcp --url http://127.0.0.1:8288

Then just ask: "what are the top USDC holders?" - the agent writes the SQL and runs it against your nest. (Making that correct on the first try is the semantic-layer work.)

Teach your agent to build nests too. Install the builder skill and an agent can drive nuthatch itself - init, config, factories, compliance, multi-nest runtimes, troubleshooting - before you even have a nest:

sh
cp -r skills/nuthatch-builder ~/.claude/skills/   # or your repo's .claude/skills/

Its CLI/config references are generated from the binary and CI-checked for drift, so the skill never lies about a flag (RFC-0017).


Everything else it can do

The core is "your contract → SQL." Beyond that, nuthatch has a full feature set for teams and operators who need more - none of it in the way of the happy path:

  • Many contracts, one nest. Declare several contracts in nuthatch.toml; index them together.
  • Contract state, pinned (RFC-0023). A [[calls]] block reads a contract at a fixed block and stores the result as a table, optionally with calldata built from the row that triggered it - the contract.balanceOf(event.params.user) a subgraph would write. Pinning the block is what keeps it deterministic: the answer is fixed, so two operators re-running the same nest get the same bytes, and the result is content-addressed on (chain_id, block, contract, calldata). Needs --state-rpc pointed at an archive node.
  • IPFS documents, verified (RFC-0037). An [[ipfs]] block turns a column of content addresses into a table of resolved documents. Every body is re-hashed and checked against the CID it claims to be, so a gateway serving the wrong bytes yields no row rather than a plausible one. The CID is taken from whatever shape the contract stored - a bare CID, an ipfs:// URI, a gateway URL, or a raw 32-byte digest - and the host is discarded, because that string came from a log and honouring it would let whoever emitted the event choose what your indexer connects to.
  • Factory / dynamic contracts (RFC-0009). Watch a factory (e.g. a pool factory); children are discovered at runtime and indexed into shared {template}__* tables - no redeploy per child.
  • Derivation, three speeds. Decoded events are tables, sealed as they index. Three built-in relations - balances, exposure, velocity - are incremental DBSP circuits; a reorg is a retraction. Nest-authored views/*.sql are named SQL evaluated at query time over hot ∪ sealed, not IVM. And a nest can declare its own authored incremental entities in entities.toml (RFC-0041): a SELECT that DBSP maintains as blocks arrive, served from /derived and queryable by name from /sql, with reorgs handled as retractions like the built-ins. On a real nest that took a panel from 2.15 s to 88 ms. A WASM transform layer remains the imperative escape hatch.
  • Compliance pack (RFC-0008). Address labels, sanctions/watch-list screening, threshold & velocity flags, counterparty-exposure views, and a signed, replayable audit manifest.
  • Alerts & webhooks (RFC-0010). HMAC-signed egress with a durable at-least-once outbox; a slow endpoint never blocks indexing.
  • Built-in admin UI. A self-contained page at /_admin/ - status, tables, view/nest inspector. Localhost-open; off-localhost it requires a token per request.
  • Many nests, one runtime, one or more chains (RFC-0012, RFC-0021). Host many nests in one process; nests on the same chain share a single cursor and one getLogs per window (N nests for roughly one nest's RPC cost), and a runtime can span multiple chains with one isolated cursor per chain - a Base nest and an Arbitrum nest in one runtime. Per-nest isolation, and a footprint budget per active-chain cursor (≤2 GB). A capability, not a mandate: one chain per runtime stays the simple default.
  • Mount and unmount nests without a restart (RFC-0027). Changing a runtime's nest set used to mean editing config and restarting, which stops every co-tenant nest too - so the blast radius of a config change was larger than that of a fault. Now POST /_admin/nests mounts one and DELETE /_admin/nests/<name> unmounts one, live. A mount is admitted only if it fits the cursor's RAM budget (refused, never warned - a budget that can be quietly exceeded is not a budget), catches up before it joins so it never drags co-tenants back through history, and only then gets routes. An unmount is a drain, not a route removal: the cursor finishes its window and releases the store before anything is torn down. The set is persisted to mounts.toml, so a restart converges on what you last asked for. An unmount keeps the dataset, so a remount is free; ?reclaim=true on the DELETE removes it once no mount references it, and DELETE /_admin/datasets/<nid> reclaims one unmounted earlier. A runtime may start with nothing mounted: declare its chains under [[chains]], and the first mount onto a chain starts that chain's cursor, dialling its RPC only then. Started with --registry, a runtime fetches a mounted NID it does not hold, verifies it as nest load does, and installs it at data/<nid>/ first. A mount answers 202 at once, and GET /_admin/mounts/<name> reports it fetching, joining, live, or failed with the reason, across a restart; ?wait=true answers only when it is done, with 507 for a breached budget. POST /_admin/suspend/<name> takes a mount off its cursor and answers 503 in its place, keeping its data and record across a restart; POST /_admin/resume/<name> catches it up from where it stopped. ?dry_run=true on a mount reports its chain, backfill, per-block RPC work and projected footprint, and the refusal a real mount would give, mounting nothing. POST /_admin/move/<name> with a new nid catches the new nest up beside the old one, then switches the name in one step: a reader sees the old nest, then the new, and never an error between.
  • Scaled mode - a fleet across machines (RFC-0022). When one box can no longer hold your cursors, or when serving and ingestion want to scale independently, the same crates run as three roles: a control plane holding what should run, a writer pool (nuthatch worker) whose members take cursor leases, and a query-FE tier (nuthatch serve) that serves from shared state and owns nothing. A role flag, never a fork - and opt-in at build time (--features postgres-store), so the published binary carries no database driver and embedded mode stays a single file with zero services. The writer pool is safely scalable because ownership is enforced by the store: every write carries a fence, and a stalled worker that wakes up finds its writes refused rather than merely discouraged. Nests are added and removed over HTTP with no restarts, versions are pinned fleet-wide so two FE nodes can never serve the same endpoint from different schemas, and runtime secrets are injected at mount - scoped to the nests a worker actually holds, write-only, and never baked into a content-addressed bundle. A worker pulls the nests it is assigned from a registry, because the machine the scheduler picks may have nothing on disk; with a bundle_hash pinned the fetch is by content address, so re-tagging a version in a registry cannot change what a fleet runs. This is the self-hosted distributed path for one operator's cooperating nests; per-tenant billing and authz between untrusting paying customers stay firmly out of scope.
  • Nest bundles + registry - bundle one, publish it, load it anywhere. nuthatch nest bundle packs a nest's authored inputs into one portable, content-addressed .bundle; nest load <bundle-or-url> verifies and installs it - regenerating the decode registry and asserting it matches - so anyone runs your exact nest, hash-verified. Share at scale with a registry (RFC-0019): nest publish <bundle> --registry <path|s3://…> --as name@version, then nest load name@version --registry … - a filesystem path or any S3-compatible bucket (MinIO/S3/R2, via AWS_* env), with private nests behind your bucket's auth. Self-hosted-first: the registry is decoupled and never mandatory - a self-built bundle and load <file|dir> need no registry at all. S3/MinIO/R2 is built in - configure it with the usual AWS_* env (AWS_ENDPOINT for non-AWS), verified live against Hetzner Object Storage.
  • Mirror a nest to a bucket (RFC-0052). nuthatch publish sync --target s3://bucket/prefix copies a nest's sealed Parquet segments, its catalogue and a provenance envelope to any S3-compatible bucket or a directory, and dev --publish-target keeps the mirror current as segments seal, uploading in streamed parts so ingestion does not wait on the bucket. The mirror is keyed by the nest's data identity, not its NID: an edit that moves the NID but not the data identity, which is the cosmetic case "Safe upgrades" below describes, keeps publishing to the same dataset, and any edit that changes what is decoded forks a new one. publish status says what is still to upload, publish verify checks every object against the local segment (--deep re-downloads and re-hashes), and doctor --publish puts the mirror in a health check. Reading it needs no nuthatch: DuckDB, Trino or anything that reads Parquet, as Reading a published nest describes.
  • Dune queries for a nest (RFC-0055). nuthatch emit dune --dir <nest> --out <dir> --source <namespace> writes one DuneSQL query per event table, casting every column to its DuneSQL type: 256-bit values to uint256/int256, addresses and hashes to varbinary, block timestamps to timestamp. It is offline and deterministic and writes nothing into the nest. Getting the rows into Dune is yours to arrange; the queries read dune.<source>.<table>.
  • Safe upgrades - no resync tax (RFC-0020, RFC-0033). Updating a nest is not a subgraph-style genesis resync, and in 2.0 it needs no command to remember. The runtime classifies the update when a nest's identity changes: compatible (additive only) is applied, breaking (a consumer-observable change - a dropped column, a removed table) is named and refused until you say --allow-breaking. Grafting does the rest: a cosmetic edit - a comment, a renamed view, a doc change - moves the nest's identity and adopts the existing dataset, so nothing re-indexes. Segments are content-addressed and shared across the runtime, so two nests that decode the same contract hold one copy, not two. What a subgraph pays a full resync for, nuthatch answers with a hash comparison.
  • Derive-first - the eth_call you don't need (RFC-0023). >70% of subgraphs call eth_call for reads that are derivable from the events they already index - they fetch only because they have no way to derive. Nuthatch does: nuthatch recipe add total_supply drops in a SQL view that computes an ERC-20's totalSupply() as Σ minted − Σ burned from Transfer events - deterministic, free, no archive node. That view runs at query time; it is not a DBSP circuit. It derives what a subgraph pays an archive node to fetch. For the handful of reads that aren't derivable but never change - decimals/symbol/name - nuthatch metadata fetch calls once and caches forever.
  • Ingestion that survives real providers (RFC-0028). An oversized eth_getLogs is split and retried, taking the provider's own suggested range when it offers one; a failure we cannot classify is split once anyway, so an endpoint whose phrasing we have never seen still works rather than stalling. Rate limits, transport blips and credential rejections are told apart - a rejected API key is cooled down loudly instead of retried forever. And sealed segments now flush on a boundary derived from the data, not from wherever a fetch window happened to stop, so two operators indexing the same range produce byte-identical segments regardless of their RPC tuning.
  • Metrics. Prometheus /metrics - tip lag, rows decoded/sealed, reorgs, query counts, RSS.

Running it in production

nuthatch is built to be fronted, not exposed raw - gateways, auth, and metering are the operator's layer; nuthatch ships the guards (query timeout, row cap, result-byte cap, concurrency limit, a filesystem-access denylist on /sql) and signals (/metrics) that make fronting it safe. It binds 127.0.0.1 by default; --listen elsewhere and put a gateway in front. See docs/operators.md.

  • Footprint: ≤2 GB RAM per active-chain cursor, single static binary, graceful SIGTERM shutdown with checkpointed resume.
  • Durability: content-addressed segments are safe to copy while running; back up the nest directory.
  • dev is the serve command - it backfills, follows the tip, and serves in one process. Copy-paste systemd and Docker recipes are in docs/operators.md.
  • Outgrown one machine? Scaled mode spreads cursors across a writer pool with an independently-scaled serving tier. Reach for it when a single box cannot hold your cursors inside its RAM budget - not before, because several nests on one machine is simpler and that simplicity is the point of the embedded path.

docs/operators.md is the full operating guide, and worth reading before you run this for real rather than after. docs/verification.md is its counterpart: an acceptance runbook that proves a deployment works, step by falsifiable step, and says plainly which levels we have verified ourselves and which we have not.

Still deciding whether to trust it at all? docs/kicking-the-tyres.md is written for that: a guide to falsifying nuthatch rather than confirming it, with the cold walk, correctness against a public subgraph, what it costs to keep running, a red-team pass on /sql, and a section listing where we have already been wrong - including two of our own security patches and an open finding. We would rather you found the next one than a user did.

The guide covers the questions people actually hit:

If you're wonderingGo to
how do I tune backfill against my RPC's limits?configuration surface - --window, --concurrency, --seal-direct
what do I scrape, and what should page me?observability - metrics, alerts, health vs readiness
what happens when something breaks?the failure model and the runbook
how do I back this up?data lifecycle
how do I run an unlisted chain?running an unlisted EVM chain
what isn't finished yet?known gaps - stated plainly

What a stable release means here

A major version is a promise about stability, not a claim of completeness.

  • 4.x is the stable line. Within 4.x, nuthatch.toml, mounts.toml and entities.toml keep working; a data directory upgrades drop-in, with no re-index; and the HTTP, SQL and MCP surfaces do not break. Upgrade only: a downgrade is not promised. Off-by-default cargo features are experimental and not covered. The full terms are the stability contract.
  • Monthly minors, immediate fixes. A released 4.x only gets patch releases. Features wait for the next monthly minor (4.1, 4.2, ...); correctness and security fixes ship at once as patches.
  • Upgrades are a binary swap. No data migration, no conversion step. Proven on a production box across 0.3.0 → 0.6.0 → 0.7.2 and at each major since, and in CI: every build opens a frozen v3.13.2 data directory and reads it back exactly (tests/upgrade_golden.rs).
  • MSRV 1.95, measured rather than asserted - it is what CI, rust-toolchain.toml and the release build all use. (Before 1.0 this file claimed 1.85, which cargo +1.85.0 check refutes in one command. A version nobody tests is not a promise.)
  • Embedded mode is the production path. dev runs in production today, whether it is hosting one nest or many. Scaled mode is built and verified across real machines, but younger - and until 0.9.3 its writer pool did not index at all. If one process per box is enough, that is still the shape to reach for.

What is deliberately not here: a hosted service, a token, telemetry, non-EVM chains, or any deployment story beyond binary + compose. Those are not backlog items; they are out of scope.

Security

nuthatch binds 127.0.0.1 by default and is built to be fronted. Before you expose /sql to anyone you do not trust, read SECURITY.md - and be on a current release:

  • v0.9.3 fixes an arbitrary file read on /sql. DuckDB accepts a quoted function name and the guard only matched an unquoted one, so SELECT * FROM "read_csv"('/etc/passwd') executed. Every earlier release is affected.
  • v0.6.2 fixes an arbitrary file write on /sql via ;-stacked COPY … TO.

Both have published advisories on the repo's Security tab. The full pre-1.0 adversary pass, including the findings we closed as not ours to fix and why, is in docs/security-audit-2026-07-31.md.


Project

  • Design lives in RFCs (0001-0061, statuses in the index); the north star and the CLI/UX direction are RFC-0015. Deferred/leftover work is in docs/backlog.md; the running log is docs/progress-log.md.
  • Governance: a grant-funded public good (NLnet / EF-ESP). No hosted service, no token, no phone-home. See GOVERNANCE.md and the standing design brief CLAUDE.md.
  • Out of scope: a hosted/metered service, non-EVM chains before EVM is airtight, or any deployment story beyond binary + compose.

License

Licensed under either of MIT or Apache-2.0 at your option.

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in this work by you shall be dual licensed as above, without any additional terms or conditions.


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  1. v4.0.0LatestOct 1, 2026